One of the best ways of getting started with Azure ML is to setup workflows with data and allow students to ‘fill-in-the-blanks’, maybe comparing how different ML algorithms perform on the same problem.

Datasets and access to data for ML

There is a plethora of sample datasets built into ML Studio for you to create educational material around, as well as many tutorials already built by the community published in the gallery.

There is a free tier that includes 10GB of Azure storage for our datasets, and ability to build Azure ML experiments for an hour with up to 100 modules. Get started with this here.

Azure for Education is for Faculty running courses using Azure, including Azure ML. Each student receives $100 of Azure credit per month, for 6 months. The Faculty member receives $250 per month, for 12 months. You can apply anytime at http://www.microsoftazurepass.com/azureu

Azure Machine Learning for Research is for University Faculty running data science courses who may need greater amounts of Azure storage and additional services such as HDInsight (Hadoop and Spark) or DocumentDB (NoSQL). Proposals are accepted every two months, you can find out more and apply at http://research.microsoft.com/en-us/projects/azure/ml.aspx